Accurate predictions of electro-optical imager performance (in terms of the range at which the imager will detect a target) are important for several reasons. The predictions serve as a guide for system development by providing a means for comparing different systems while still in their design phase, and they can be used to decide if systems with a specific design will meet established requirements. The predictions are also used in war game simulations that directly influence the development of engagement tactics. Thus, it is very important to be able to model the performance of sensors, in terms of the probability that they will detect a given target at a particular range.
One of the primary modeling techniques known in the prior art is the ACQUIRE model. The ACQUIRE model uses several parameters in order to develop an empirical Target Transfer Probability Function (TTPF). The TTPF then predicts the probability of detection for the particular target at various ranges with some confidence.
The ACQUIRE model, however, suffers from certain limitations. Specifically, camouflaged and reduced signature targets have long presented problems for modeling target acquisition performance, and the ACQUIRE model loses integrity when the target is thermally camouflaged. Stated differently, the ACQUIRE method for comparing sensor performance is relatively insensitive to target temperature contrast, and field studies have determined that the ACQUIRE method generally overestimates the range at which low thermal contrast targets are detected. This inaccuracy in prediction modeling has hampered the evaluation of camouflage effectiveness, and it hinders the development of engagement tactics for various weapons systems.
To compensate for the above limitation, one solution often used by war gamers involves adjusting the ACQUIRE cycle criterion, or the ACQUIRE N50 variable, in accordance with available data for the vehicle of interest or its surrogates. N50 describes the number of cycles across a target that must be resolved to achieve a 50 percent probability of detection. For example, the standard manner of accounting for parameters that the ACQUIRE method does not directly model (for example, target motion, varying scene clutter levels and camouflage) has typically been to decrease the ACQUIRE cycle criterion, N50, for moving targets (moving targets are easier to spot) or increase the N50 cycle criterion for camouflaged vehicles (which has the effect of making them more difficult to spot). But it has heretofore been unclear how much N50 must be adjusted to achieve an accurate prediction. If N50 is increased too much, an underestimation of sensor performance results. Conversely, if the ACQUIRE methodology described above is used to predict the detection range of a thermally camouflaged target, an inaccurate prediction results. A further disadvantage of requiring special test and/or analyses for each situation is that it leads to great inefficiencies and long delays associated with acquiring appropriate data for use in estimating lower contrast target performance.
In light of the above, it is an objective of the present invention to provide a method for predicting the detection range of low thermal contrast targets. It is another objective of the present invention to provide a method for accurate modeling of thermal sensor performance in the detection of a thermally camouflaged target. Yet another objective of the present invention is to provide a method for target acquisition modeling which predicts sensor performance against low thermal contrast (camouflaged) targets without perturbing the prediction performance against high thermal contrast (uncamouflaged) targets. Yet another objective of the present invention is to provide a modeling method which more accurately predicts sensor performance against low contrast targets without requiring highly detailed knowledge of the scenario within which the detection takes place. It is another goal of the present invention to provide a method for modeling of target acquisition and prediction which can be accomplished relatively easily in a cost-effective manner.